Open AccessAdvancing Computer-Aided Drug Discovery (ACADD): In-Silico Approach towards Nuclear Receptors by Big Data
Author(s) -
K. Palaniammal,
M. Saravana Roentgen Mani,
Rupesh Kumar
Publication year - 2021
Publication title -
journal of pharmaceutical research international
Language(s) - English
Resource type - Journals
ISSN - 2456-9119
DOI - 10.9734/jpri/2021/v33i30a31612
Subject(s) - in silico , drug discovery , computational biology , betulinic acid , chemistry , drug , docking (animal) , ligand (biochemistry) , nuclear receptor , drug development , receptor , pharmacology , combinatorial chemistry , biochemistry , biology , medicine , transcription factor , genetics , nursing , gene
The progression of drug discovery and development is time consuming and costly. Advancing Computer-aided drug discovery (ACADD) is an effective tool in reducing the time and cost of research and development. This study deals with the evaluation of the nuclear receptors for the in-silico biological activity using ligand betulinic acid and dexamethasone. Docking results showed that binding energy was -74.190 kcal/mol when compared with that of the standard (-51.551 kcal/mol). Interaction energy -44.16 & -25.14 kcal/mol) of the ligands also coincide with the binding energy. These ligands have shown the best ligand-receptor interaction based on their structural parameters.